The development of perennial grain crops is driven by the vision of simultaneous food production and enhanced ecosystem services. Typically, perennial crops like intermediate wheatgrass (IWG, Thinopyrum intermedium) have low seed yield and other detrimental agronomic traits. Next generation sequencing has made genomic selection (GS) a tractable and viable breeding method. To investigate how an IWG breeding program may utilize GS, we evaluated 3,658 plants over two years for 46 traits to build a training population. Six statistical models were used to evaluate the non-replicated data, and a model using autoregressive order 1 (AR1) spatial correction for rows and columns combined with the genomic relationship matrix provided the highest estimates of heritability. Genomic selection models were built using 18,357 single nucleotide polymorphism (SNP) markers from genotyping-by-sequencing, and a 20-fold cross-validation showed high predictive ability for all traits (r > 0.80). Prediction accuracies improved with increasing training population size and higher marker numbers, even with larger amounts of missing data per marker. Based on these results, we propose a GS breeding method that is capable of completing one cycle per year compared to a minimum of two years per cycle with phenotypic selection. We estimate this breeding approach can increase the rate of genetic gain up to 2.6 times above phenotypic selection for spike yield, allowing GS to enable rapid domestication and improvement of IWG and other novel species.

See article for details and README.pdf for code and documentation of methods.